Table of Contents
ISRN Sensor Networks
Volume 2014 (2014), Article ID 518268, 10 pages
http://dx.doi.org/10.1155/2014/518268
Research Article

An Energy Efficient Data Gathering in Dense Mobile Wireless Sensor Networks

1CSE Department, Anna University, Regional Centre, Coimbatore, Tamilnadu 641047, India
2ECE Department, Coimbatore Institute of Engineering and Technology, Coimbatore, Tamilnadu 641109, India

Received 6 February 2014; Accepted 20 March 2014; Published 16 April 2014

Academic Editors: G. Mazzini, A. Song, and Y. Yu

Copyright © 2014 R. Velmani and B. Kaarthick. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Amidst of the growing impact of wireless sensor networks (WSNs) on real world applications, numerous schemes have been proposed for collecting data on multipath routing, tree, clustering, and cluster tree. Effectiveness of WSNs only depends on the data collection schemes. Existing methods cannot provide a guaranteed reliable network about mobility, traffic, and end-to-end connection, respectively. To mitigate such kind of problems, a simple and effective scheme is proposed, which is named as cluster independent data collection tree (CIDT). After the cluster head election and cluster formation, CIDT constructs a data collection tree (DCT) based on the cluster head location. In DCT, data collection node (DCN) does not participate in sensing, which is simply collecting the data packet from the cluster head and delivering it into sink. CIDT minimizes the energy exploitation, end-to-end delay and traffic of cluster head due to transfer of data with DCT. CIDT provides less complexity involved in creating a tree structure, which maintains the energy consumption of cluster head that helps to reduce the frequent cluster formation and maintain a cluster for considerable amount of time. The simulation results show that CIDT provides better QoS in terms of energy consumption, throughput, end-to-end delay, and network lifetime for mobility-based WSNs.